Trust and delivery for company-controlled AI

See how hosting, model ownership, fallback rules, and change control stay explicit before launch.

Hosting choice

The first workflow can run in private cloud, VPC, or on-prem depending on fit, data needs, and how much control the company requires.

Model approach and exception path

Equ usually starts with open models, then decides whether prompting, retrieval, tuning, or fine-tuning fits the workflow. Ambiguous or low-confidence cases escalate to human review instead of disappearing inside automation.

Audit capture and rollback rule

Overrides, decisions, policy changes, and model changes stay visible after launch. If quality drops too far, the team should be able to pause, narrow, or revert the workflow.

What Equ does not claim

Equ does not claim fake customer logos, formal certifications that are not in place, full autonomy where review matters, founder public work as client proof, universal API-vendor failure, or outage-free independence.

Next step

Request Workflow Review when the workflow and owners are clear, or use the Workflow Fit Assessment to score fit before a buying conversation.